Title :
GARCH model-based large-scale IP traffic matrix estimation
Author :
Jiang, Dingde ; Hu, Guangmin
Author_Institution :
Lab. of Broadband Opt. Fiber Transm. & Commun. Networks, Univ. of Electron. Sci. & Technol. of China, Chengdu
fDate :
1/1/2009 12:00:00 AM
Abstract :
This letter proposes a novel method to estimate large-scale IP traffic matrix (TM). By using the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) to model the Origin-Destination (OD) flows, we can easily get rid of the ill-posed problem of large-scale IP TM. Compared with previous methods, our method does not only hold the lower estimation errors but also is more robust to the noise.
Keywords :
IP networks; autoregressive processes; matrix algebra; telecommunication traffic; estimate large-scale IP traffic matrix; generalized autoregressive conditional heteroscedasticity model; large-scale IP traffic matrix estimation; origin-destination flows; Equations; Estimation error; Gravity; High-speed networks; IP networks; Large-scale systems; Noise robustness; Routing; Telecommunication traffic; Traffic control; Traffic matrix, traffic matrix estimation, traffic engineering, GARCH, nonstationary traffic.;
Journal_Title :
Communications Letters, IEEE
DOI :
10.1109/LCOMM.2008.081271
